W M Rice University
Head of Venture Acceleration, Program Manager
United States
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About the role
- This is a unique opportunity to be at the forefront of innovation and help Rice entrepreneurs bring their cutting-edge ideas to market.
- You will work closely with student startup founders to help them accelerate their growth, secure funding, and achieve their goals while acting as connective tissue to the broader Texas and US startup ecosystems.
- Lilie is a small, ambitious team that works collaboratively to achieve amazing results, employing an iterative creation process where we share our work early and often.
Requirements
- Most employment activities are required to be performed in-person and on-campus.
- Bachelor's degree
Skills
- Ability to develop and initiate new strategies
- Adept at problem solving, creating contingency plans and handling issues when necessary
- Excellent organizational and time management skills
- Excellent verbal and written communication skills
- Excellent client service orientation
- Ability to prioritize, take initiative, and ownership of projects
- Ability to routinely and independently exercise sound judgment in making decisions
- Five or more (5+) years of entrepreneurship, program management experience
- Experience with startups and startup accelerator programs
- Experience engaging within and across a startup ecosystem
- Shares work early and often, valuing a process of iterative feedback to produce exceptional results
- Preferences:
Compensation
- $95k-$105k
Benefits
- https://knowledgecafe.rice.edu/benefits
Company info
- We value a highly collaborative and community-based culture, with expectations to provide in-person support and services to all members of our community.
Equal opportunity
- If an applicant requires a reasonable accommodation for any part of the application or hiring process, please get in touch with Rice University's Human Resources Office via email at facstaffada@rice.edu for support.
This listing is sourced directly from W M Rice University's careers page and normalized into a canonical job model.